Lead Engineer - Generative AI Product Engineering (Remote Eligible)
at Capital One
McLean, Virginia, USA -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 30 Oct, 2024 | Not Specified | 07 Aug, 2024 | 1 year(s) or above | Optimization Techniques,Computer Science,Availability,Azure,Sdks,Aws,Platforms,Fms,Design,Ease,Customer Experience,Neural Networks,Security,Training,Engineers,Python,Computer Engineering,Access Control,Scalability,Kubernetes | No | No |
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Description:
Center 3 (19075), United States of America, McLean, Virginia
Lead Engineer - Generative AI Product Engineering (Remote Eligible)
Lead Engineer - Generative AI Product Engineering (Remote Eligible)
Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
We are looking for an experienced Lead Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include:
- Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs.
- Design APIs for performance, real-time applications, scale, ease of use and governance automation.
- Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience.
- Enable our users to build new GenAI capabilities.
- Develop tools and processes to monitor API access patterns and operational health.
- Design and implement AI safety and guardrails in the API layer working closely with researchers.
BASIC QUALIFICATIONS:
- Bachelor’s degree in Computer Science, Computer Engineering or a technical field
- At least 6 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques
- At least 6 years of experience programming with Python, Go, Scala, or Java
- At least 1 years of experience building, scaling, and optimizing training or inferencing systems for deep neural networks
PREFERRED QUALIFICATIONS:
- Familiarity with building large-scale AI and ML products or platforms serving millions of users.
- Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.
- Experience with Kubernetes and KubeFlow workloads is preferred.
- Familiarity with the Model Development Lifecycle and MLOps preferred.
- Experience architecting cloud systems for security, availability, performance, scalability, and cost.
- Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines.
- Experience at tech and product-driven companies/startups preferred.
- Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities.
- Have experience with API security, observability, cloud access control and privacy best practices.
- Familiarity with deploying AI or ML models in demanding production environments.
Responsibilities:
Please refer the Job description for details
REQUIREMENT SUMMARY
Min:1.0Max:6.0 year(s)
Information Technology/IT
IT Software - System Programming
Software Engineering
Graduate
Computer science computer engineering or a technical field
Proficient
1
McLean, VA, USA